Since the inception of Industry 4.0 in 2012, emerging technologies have enabled the
acquisition of vast amounts of data from diverse sources such as machine tools, robust and …

The results obtained in the wafer test process are expressed as a wafer map and contain
important information indicating whether each chip on the wafer is functioning normally. The …

The detection of defects using inspection systems is common in a wide range of
corporations such as semiconductor industries. The use of techniques based on deep …

This paper considers the use of a machine learning system for the reconstruction and
recognition of distorted or damaged patterns, in particular, images of faces partially covered …

There are mainly two types of wafer map failure pattern recognition, ie, traditional
classification based and deep learning based approaches. Traditional classification usually …

In wafer map defect pattern recognition, deep learning methods are predominantly used.
These models autonomously learn features without explicit human intervention due to their …

Building and updating tree inventories is a challenging task for city administrators, requiring
significant costs and the expertise of tree identification specialists. In Ecuador, only the Trees …

The accurate and automatic inspection of wafer maps is vital for semiconductor engineers to
identify defect causes and to optimize the wafer fabrication process. This research work …

Accurately assessing image quality is a challenging task, especially without a reference
image. Currently, most of the no-reference image quality assessment methods still require …

Due to the complexity and dynamics of the semiconductor manufacturing processes, wafer
bin maps (WBM) present various defect patterns caused by various process faults. The …